Name
Title | ||
|---|---|---|
A Kernel-Based Nonparametric Regression Method for Clutter Removal in Infrared Small-Target Detection Applications |
Abstract | ||
|---|---|---|
Small-target detection in infrared imagery with a complex background is always an important task in remote-sensing fields. Complex clutter background usually results in serious false alarm in target detection for low contrast of infrared imagery. In this letter, a kernel-based nonparametric regression method is proposed for background prediction and clutter removal, furthermore applied in target detection. First, a linear mixture model is used to represent each pixel of the observed infrared imagery. Second, adaptive detection is performed on local regions in the infrared image by means of kernel-based nonparametric regression and two-parameter constant false alarm rate (CFAR) detector. Kernel regression, which is one of the nonparametric regression approaches, is adopted to estimate complex clutter background. Then, CFAR detection is performed on “pure” target-like region after estimation and removal of clutter background. Experimental results prove that the proposed algorithm is effective and adaptable to small-target detection under a complex background. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/LGRS.2009.2039192 | IEEE Geosci. Remote Sensing Lett. |
Keywords | Field | DocType |
infrared imagery,remote sensing,adaptive detection,image representation,cfar detection,kernel-based nonparametric regression method,regression analysis,infrared imaging,complex clutter background estimation,kernel regression,clutter removal,infrared small-target detection,linear mixture model,infrared detectors,clutter background prediction,target detection,remote sensing field,constant false alarm rate (cfar),object detection,two-parameter constant false alarm rate detector,clutter,infrared image,shape,constant false alarm rate,filtering,pixel,kernel,infrared,thyristors,concrete,nonparametric regression,fluctuations | False alarm,Nonparametric regression,Remote sensing,Artificial intelligence,Kernel regression,Kernel (linear algebra),Computer vision,Object detection,Pattern recognition,Clutter,Constant false alarm rate,Mixture model,Mathematics | Journal |
Volume | Issue | ISSN |
7 | 3 | 1545-598X |
Citations | PageRank | References |
28 | 1.60 | 5 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yanfeng Gu | 1 | 742 | 55.56 |
| Chen Wang | 2 | 108 | 5.96 |
| BaoXue Liu | 3 | 28 | 1.60 |
| Ye Zhang | 4 | 28 | 1.60 |